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Record W3209735260 · doi:10.32920/ryerson.14639052.v1

Development of a Polymer Extrusion System to Manufacture Recycled Bioplastic Composites for Additive Manufacturing

2021· preprint· en· W3209735260 on OpenAlexafffundabout
Jordan Kalman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsToronto Metropolitan University
FundersMcGill University
KeywordsMaterials scienceExtrusionUltimate tensile strengthComposite materialPlastics extrusionThermoplasticTextileFiberBioplasticTurbine bladeRaw materialTurbineWaste managementMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

The research validates the use of recycled end-of-life wind turbine blade fiberglass to improve the mechanical strength of a thermoplastic in collaboration with McGill University. The critical fiber length glass fibers from wind turbine blades are reclaimed through a mechanical grinding process, incorporated with polylactic acid (PLA) in a twin-screw extruder to produce composite pellets and manufactured into filament via a single-screw extrusion system. This filament is used as feedstock for standard fused filament fabrication (FFF) 3D printers to manufacture ASTM standard tensile specimens: D638-14. Reinforced thermoplastic filaments with varying fiber content ranging from 3%-10% are manufactured using this process. It was found that the long fiber reinforced PLA provided a 20% increase in tensile strength and a 28% increase in the stiffness compared to the pure PLA specimens. The increased strength and stiffness can allow the material to be used in smaller quantities when replacing a given thermoplastic material. This material could be beneficial for both rapid prototyping and application-specific products. In addition to the issues faced with the waste management of wind turbines, so too is the textile waste caused by the improper disposal of clothing. To address the issues faced with improper disposal of clothing, a material characterization method for analyzing the draping behaviour of flexible 3D printed textiles was initiated. Pairing an extrusion system with 3D printing allows for the most rapid development of both a specialized material and engineering solution. Looking to the future of the textile industry, it is crucial that sustainable recycling and manufacturing processes are used to create a better future for the generations to come. Keywords: Sustainability, Recycling, The Wind Energy Industry, Wind Turbine Blades, Lifecycle Analysis, Circular Economy, 3D Printing, Additive Manufacturing, Bioplastic, Polylactic Acid, Extrusion, Single-Screw Extruder, Fiber Reinforced Filaments, ASTM D638 Coupons.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.225
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes3
Has abstractyes

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